Degradation of the Vaccine Additive Thimerosal by L-Glutathione and L-Cysteine at Physiological pH
Bibliographic record
Abstract
Humans are being exposed to a variety of potentially toxic metal compounds through the diet and/or the intravenous administration of metal-containing medicinal drugs. The organomercurial thimerosal (THI) is a bactericidal that is present in vaccines, but its potential degradation by biomolecules in vivo is incompletely understood. To probe its interaction with low-molecular-weight thiols that are highly abundant within cells, we have employed an LC-based analytical approach in conjunction with a mercury-specific detector. The injection of THI into a C18-HPLC column equilibrated with mobile phases that contained increasing concentrations of up to 15 mM of glutathione (GSH) and 30% acetonitrile revealed the elution of a GS-EtHg adduct in conjunction with THI, as evidenced by electrospray ionization mass spectrometry. These results were confirmed by 199Hg-NMR spectroscopy. While these results imply a rapid degradation of THI by GSH at physiological pH, it is important to point out that our results were obtained in aqueous solutions containing 30% (v:v) acetonitrile. Further studies need to confirm if the GS-EtHg adduct is also formed in biological fluids. Our results nevertheless demonstrate that GSH and L-cysteine (Cys) are potential targets of THI at physiological pH, which is relevant to better understand its side effects, including previously reported effects on Ca2+ channels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".